Ocean exchanges with the atmosphere

Ocean exchanges with the atmosphere

Peter K. Taylor

Southampton Oceanography Centre

UK

….did we learn anything during WOCE?

OverviewWhat surface fluxes were needed for WOCE

How the flux estimates are obtained

How far have we progressed during the WOCE period

Wind StressHeat Fluxes

Future Flux Observing System

““Separately for…”Separately for…”

The Goals of WOCENeed heatand freshwater fluxes

Need wind stress

The important Air-Sea fluxes for WOCE

““Net heat fluxNet heat flux is sum of…”is sum of…”


““but little in this talkbut little in this talkon precipitationon precipitation since accuracy since accuracy

still poor” still poor”


Goal 2 of WOCENeed climatological flux fields

Need to develop Observing System

Air-Sea Flux aims for WOCE

Produce estimates of the global air-seafluxes of heat, freshwater and momentumon a range of time and space scales

Work toward definition of an on-going observing system for the surface fluxes

Produce climatological fields for these fluxes

How surface fluxes are determined

Budget methods give total heat flux:

divergence of ocean heat transport (e.g. Ganachaud & Wunsch, 2000)

atmospheric flux divergence with top of atmosphere radiative balance …the “residual” method(e.g. Trenberth et al. 2001 )

Determining the individual flux components

Turbulent fluxes from in situ data, models, and satellites, are based on meteorological variables (temperature, wind, etc.) and the bulk formulae

SW and LW Radiative fluxes can be obtained from Satellite data and from NWP models

Example of Bulk FormulaLatent heat flux (W/m2)

Flux = Transfer x Wind x humidityCoefficient speed difference

CE depends on the roughness length(s) and stability ( z / L )

Determining the Transfer Coefficient

GATE (1974)

SeaSat (1978) JASIN (1978)

GARP Air-Sea Interaction experiments :BOMEX, AMTEX, IFYGL

““SeaSat coincidedSeaSat coincidedwith JASIN”with JASIN”

The Legacy of GARP: Budget experiments are difficult!

Experimental data on transfer coefficients was available

Satellite scatterometers could define wind forcing

We must continue to maintain (and improve) the in situ observing systems

The Legacy of SeaSat:

Developing the Voluntary Observing Ship (VOS) system

Mean random errors in ship SST obs ( C )1970 - 1997 (Kent, 2002)

The random and systematic errors in VOS data are much better known

1.4

1.41.41.21.00.9

1.41.3

1.0

1.51.81.3

1.21.32.0 1.4

1.41.60.9

Due to research during the WOCE period (partly funded by TOGA and WOCE):

Now greater emphasis on meta-data ….how the observations are obtained

““we can now plotwe can now plot a map of error valuesa map of error values

like this one”like this one”

Wind Stress

The choice of Drag Coefficient, CD10n

Effect of using other CD10n values

Climatic variations in mean wind stress

Effect of poor sampling in the SO

The variation of the Drag Coefficient with wind speed

Observations

Models““Before WOCE:Before WOCE:Smith (1980)”Smith (1980)”

““Smith (1988) …used for Smith (1988) …used for TOGA and scatterometerTOGA and scatterometer

Data on WOCE DVD”Data on WOCE DVD” ““WOCE Southern Ocean WOCE Southern Ocean Cruises confirmed Cruises confirmed

Smith (1980)” Smith (1980)”

““but some models arebut some models arestill using thesestill using thesehigher values” higher values”

Comparison of the zonal mean

wind stress

( Josey et al. 2002, J.Phys.Oceanogr. 32,1993 - 2019)

55N to 30S:H & R have higher stress values due to the larger drag coefficient


wind stress


High northern Latitudes show effect of different sampling periods

Change in wind stress with NAOSOCH&R

““SOC & H&R windSOC & H&R windstress fieldsstress fieldslook similar”look similar”

Change in wind stress with NAOSOCH&R

1949-79

NCEP

H&R / 1.32

1980-93

““but NCEP has lowerbut NCEP has lower stress for periodstress for period

representing mostrepresenting most of H&R data” of H&R data”

““Scaling H&R by CdScaling H&R by Cdratio gives valuesratio gives valuessimilar to NCEP”similar to NCEP”

““Apparent agreementApparent agreementbetween H&R & SOCbetween H&R & SOC

was due to NAOwas due to NAOvariations” variations”

‘‘remaining differences remaining differences between NCEP, H&R between NCEP, H&R and SOC may be due and SOC may be due

to bad sampling”to bad sampling”


wind stress


Southern Ocean:due to poor sampling in situ climatologies have lower stress values compared to models

(or to satellite data)

Zonal Wind stress in the Southern

Ocean: July mean values

SOC Climatology

ECMWF

ERS-1AMI -2 -1 0 1 2 3 4

( 10-1 N/m2 )

-5 0 5 ( 10-1 N/m2 )

““ECMWF ERA and ECMWF ERA and scatterometer winds scatterometer winds show extensive belt show extensive belt of high winds in SO”of high winds in SO”

““Where data is lacking Where data is lacking values are extrapolated values are extrapolated

from other regions”from other regions”

Summary: Wind stress The WOCE cruises have helped confirm the Smith (1980) CD10n to U10n relationship

H&R (and Oberhuber) over-estimate the wind stress over much of the world ocean: by around 30%

….but we knew that (e.g. Harrison, 1989)…so why do models still use these stress fields?The magnitude and patterns of wind stress varies significantly between different periods: WOCE will not be “typical” of other decades

WOCE helped implement satellite scatterometer missions which are now coming to fruition

Heat FluxesGlobal Heat balance for in situ climatologies

Adjustment using WOCE hydrography

Comparison with other estimates: Reanalyses, Residual Method

Comparison of the implied latent heat flux distributions

Annual heat input to Ocean (W/m2)(SOC Climatology, Josey et al. 1999)

30 90 150 -150 -90 -30 30

75

60

45

30

15

0

-15

-

30

-45

-60

-

75

-100 -50 0 50 100 W/m2

““This annual mean is This annual mean is deceptive with regard deceptive with regard

to regions of to regions of heating and cooling”heating and cooling”

QuickTime™ and aGIF decompressorare needed to see this picture.

Monthly heat input to Ocean (W/m2)(SOC Climatology, Josey et al. 1999)

““Heating occurs over Heating occurs over most of summer most of summer

Hemisphere” Hemisphere”

““we will use we will use January fields in January fields in

following comparisons”following comparisons”

OSU(Esbensen & Kushnir 1981)

Before and after WOCE

SOC (Josey et al. 1999)

-500 -250 0 250 W/m2

Comparison of SOC & OSU climatologies

SOC has:

Correct flux averaging method

( Fluxes calculated from individual observations and then averagedi.e. “sampling” rather than “classical” )

Higher resolution More information: revised version of COADS with observations corrected on a ship by ship basis

Larger Global Heat Budget imbalance

Comparison of ClimatologiesNet Heat Flux for January and

Mean Annual imbalance (W/m2)

-500 -250 0 250 W/m2

5 30

? 0.05

““there is obviously there is obviously more summer heating more summer heating

in SOC fields”in SOC fields”

The Heat Budget problem

Unless adjusted, climatologies show too much heat flux into the ocean(e.g. Bunker et al. 1982, Isemer et al. 1989, DaSilva et al. 1984, Josey et al. 1999)

This heat imbalance varies little year to year ( few W/m2 )

Adjusting the heat fluxes degrades the comparisons with buoy data(Josey et al. 1999)

Can WOCE help?

Heat Transports in PW(adapted from Grist & Josey, 2002)

0.28 (Bacon, 97)

0.002 Aagard & Greisman (1975) 0.1

-0.09 ( R & McC. 89)

0.76 (Bryden et al. 91)

0.70 (Wijffels et al. 96)

0.90 (Wijffels et al. 2001)

1.22 (Hall & Bryden 82)

1.221.18

(Klein et al. 95)

0.60 (Speer et al. 96)

0.29 (Holfort & Siedler 01)

0.46 (McDonagh 02)

““Grist & Josey (see poster)Grist & Josey (see poster)have adjusted SOC have adjusted SOC climatology usingclimatology using

WOCE section data”WOCE section data”

Effect of Constraining Heat Budget

SOC Constrained using WOCE sections

(Grist & Josey, 2002)

-2 W/m2

SOC January net heat flux (Josey et al. 1999)

+30 W/m2

Comparison of Constrained SOC &

UWM heat fluxes

(adapted from Grist & Josey, 2002)

Implied Global Ocean heat transport (PW)

““Fields look similar but DaSilva Fields look similar but DaSilva (UWM) has e.g. stronger cooling over(UWM) has e.g. stronger cooling over

Gulf Stream, greater heating inGulf Stream, greater heating insummer hemisphere; this causes summer hemisphere; this causes

small differences in implied small differences in implied ocean heat transport… ” ocean heat transport… ”

Comparison of other Flux fields

-2 -4

61““some differences are obvious, some differences are obvious, for example the el Nino region”for example the el Nino region”

Air-SeaHeat Flux

020S50S80S 20N 50N 80N

Atlantic Zonal Mean Values

(adapted from Grist & Josey, 2002)

040S 40N

Implied Ocean Heat

Transport

““compared to SOC,compared to SOC,there is slightly more there is slightly more heating in the UWM heating in the UWM

climatology, hence less climatology, hence less ocean transport” ocean transport”

““in Residual method,in Residual method,more cooling over the more cooling over the Gulf Stream implies Gulf Stream implies greater ocean heat greater ocean heat

transport northward”transport northward”

““in contrast NCEP cooling in contrast NCEP cooling occurs in the Trade Windoccurs in the Trade Windzone rather than higher zone rather than higher

latitudes” latitudes”

““lack of net heat inputlack of net heat inputin ERA implies too largein ERA implies too large

ocean heat transport ocean heat transport in Southern Ocean”in Southern Ocean”

Atlantic OceanMean area heat flux

Climatology - WOCE( W/m2 )

(adapted fromGrist & Josey, 2002)

““area mean air-sea area mean air-sea flux can be calculated flux can be calculated

from difference in from difference in ocean heat transport ocean heat transport

between hydrographic between hydrographic lines” lines”

““Bar plot shows difference Bar plot shows difference from this mean for the from this mean for the

flux fields listed” flux fields listed”

““original SOC climatology original SOC climatology has too much heat has too much heat input everywhere” input everywhere”

““compared to hydrography, compared to hydrography, rest have too little cooling atrest have too little cooling athigh latitudes, too little heathigh latitudes, too little heat

input in low latitudes”input in low latitudes”

Pacific & Indian Oceans: Mean area heat fluxClimatology - WOCE ( W/m2 )

(Grist & Josey, 2002)

““any such pattern in the any such pattern in the Pacific is less clear”Pacific is less clear”

The Residual Method gives the best agreement with Hydrography

The in situ climatologies can be adjusted to give agreement with Hydrography

But have the individual heat flux components been properly adjusted?

Transfer Coefficient for water vapour

Review by Smith (1989) …as used in SOC climatology

Observations during WOCE period(Fairall et al. 2001)

Liu, Katsaros & Businger (1979)model …used in OSU climatology

Errors in estimating Latent Heat flux

Air-Sea interaction experiments suggest that CE10n is known to 10% or better

Inverse analyses suggest that the Flux is underestimated by nearly 20%

Do the errors in the observations explain this difference?

““possibly but we need possibly but we need independent verification”independent verification”

Independent sources for Evaluating Bias Errors

in Latent Heat Flux Estimates

Satellite based estimates of Latent Heat Flux

Flux fields from models

Reference data sets - buoys and ships

Freshwater Budget - but precipitation???

Annual mean zonal Latent Heat Flux

( from Curry et al. 2002 and Kubota et al. 2002 )

UWM/COADS NCEP/NCAR

ERA

““Constrained UWM/COADSConstrained UWM/COADSwould be similar to ERAwould be similar to ERA……model fluxes bridge model fluxes bridge

original and constrained original and constrained values”values”

““The ‘SeaFlux’ groupThe ‘SeaFlux’ grouphave performedhave performed

flux field comparisonsflux field comparisons……these are original these are original

UWM/COADS values” UWM/COADS values”

Example of a Satellite Flux field Product

Climatological mean (1988 - 1996) Latent Heat Fluxin January from the HOAPS (Grassl et al. 2000) Atlas

Annual mean zonal Latent Heat Flux

( from Curry et al. 2002 and Kubota et al. 2002 )

UWM/COADS

HOAPS (Schulz et al. 1997)

GSSTF1(Chou et al. 2001)

J-OFUROKubota et al. 2002)

““satellite derived flux fields satellite derived flux fields also show a range of values”also show a range of values”

Comparison of SOC Climatology and WHOI Buoy deployments

Arabian Sea

TOGA

FASINEX

Subduction

““Only for FASINEX is the Only for FASINEX is the constrained field (solid colour) constrained field (solid colour)

closer to the buoy values”closer to the buoy values”

Comparison of SOC Climatology and WHOI Buoy deployments

Arabian Sea

TOGA

FASINEX

Subduction

““but for short wavebut for short waveheating it is TOGA heating it is TOGA that is brought intothat is brought into

better agreement” better agreement”

Summary

Increasing the Latent Heat flux gives similar evaporation to the reanalysis results

BUT…comparison with reference data suggests the models over-estimate evaporation

We need more in situ reference data

Satellite data doesn’t help!

Beyond WOCE:the Observing System

Future Surface Flux estimation

Move toward global fields from NWP models and/or Remote sensing (wind stress, shortwave, sst, latent heat? longwave? ) Role of in situ data is increasingly for verification:

“Flux reference” BuoysImproved ship data (the VOS Climate project, VOSClim)

Using “Flux Reference” Data

Buoy data shows that a typical model over-estimates the Latent Heat Flux

Ship data extends the comparison to other areas and times

The J-COMM VOS Climate Project

VOSClim

VOSClim initially aims to improve the meta-data available from the ships

Observations during 2001 from ships recruited to the VOSClim Project

P&O Nedlloyd Southampton - a VOSClim ship

Have We Learnt Anything?

During WOCE we have learnt much about the error characteristics of our flux estimates

Mean net heat flux fields can be brought into agreement with ocean heat transport values

But we still don’t have distributions of the component heat fluxes which give a balanced budget

However…

For Surface Flux studies, the full dividend of WOCE is still to come:

Continuing analysis of WOCE data

The full exploitation of satellite data

The Global Ocean Observing System

New NWP reanalysis experiments

AcknowledgementsThe content of this talk was based on the conclusions of the joint WCRP/SCOR Working Group on Air-Sea Fluxes1. However the specific examples shown were obtained from the SOC Meteorology team2, in particular Simon Josey and Jeremy Grist; the IRI/LDEO Climate Data Library3; and the SeaFlux group4. Bob Marsh supplied the title page graphic.

3 http://ingrid.ldeo.columbia.edu/ 4 http://paos.colorado.edu/~curryja/ocean/

1 http://www.soc.soton.ac.uk/JRD/MET/WGASF/2 http://www.soc.soton.ac.uk/JRD/MET/

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Ocean exchanges with the atmosphere